[Major Update] Fooocus 2.0.0 (#346)
[Major Update] Fooocus 2.0.0 (#346)
This commit is contained in:
lllyasviel
GitHub
parent
25fed6a4fe
commit
47876aaf99
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@ -1 +1 @@
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version = '1.0.67'
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version = '2.0.0'
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@ -11,14 +11,15 @@ def worker():
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import time
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import shared
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import random
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import copy
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import modules.default_pipeline as pipeline
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import modules.path
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import modules.patch
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from modules.sdxl_styles import apply_style_negative, apply_style_positive, aspect_ratios
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from modules.sdxl_styles import apply_style, aspect_ratios, fooocus_expansion
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from modules.private_logger import log
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from modules.expansion import safe_str
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from modules.util import join_prompts
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from modules.util import join_prompts, remove_empty_str
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try:
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async_gradio_app = shared.gradio_root
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@ -29,20 +30,42 @@ def worker():
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except Exception as e:
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print(e)
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def progressbar(number, text):
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outputs.append(['preview', (number, text, None)])
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def handler(task):
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prompt, negative_prompt, style_selction, performance_selction, \
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aspect_ratios_selction, image_number, image_seed, sharpness, raw_mode, \
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prompt, negative_prompt, style_selections, performance_selction, \
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aspect_ratios_selction, image_number, image_seed, sharpness, \
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base_model_name, refiner_model_name, \
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l1, w1, l2, w2, l3, w3, l4, w4, l5, w5 = task
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loras = [(l1, w1), (l2, w2), (l3, w3), (l4, w4), (l5, w5)]
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raw_style_selections = copy.deepcopy(style_selections)
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if fooocus_expansion in style_selections:
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use_expansion = True
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style_selections.remove(fooocus_expansion)
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else:
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use_expansion = False
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use_style = len(style_selections) > 0
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modules.patch.sharpness = sharpness
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outputs.append(['preview', (1, 'Initializing ...', None)])
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progressbar(1, 'Initializing ...')
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prompt = safe_str(prompt)
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negative_prompt = safe_str(negative_prompt)
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raw_prompt = prompt
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raw_negative_prompt = negative_prompt
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prompts = remove_empty_str([safe_str(p) for p in prompt.split('\n')], default='')
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negative_prompts = remove_empty_str([safe_str(p) for p in negative_prompt.split('\n')], default='')
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prompt = prompts[0]
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negative_prompt = negative_prompts[0]
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extra_positive_prompts = prompts[1:] if len(prompts) > 1 else []
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extra_negative_prompts = negative_prompts[1:] if len(negative_prompts) > 1 else []
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seed = image_seed
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max_seed = int(1024 * 1024 * 1024)
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@ -52,63 +75,74 @@ def worker():
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seed = - seed
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seed = seed % max_seed
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outputs.append(['preview', (3, 'Load models ...', None)])
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progressbar(3, 'Loading models ...')
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pipeline.refresh_base_model(base_model_name)
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pipeline.refresh_refiner_model(refiner_model_name)
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pipeline.refresh_loras(loras)
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pipeline.clear_all_caches()
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tasks = []
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if raw_mode:
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outputs.append(['preview', (5, 'Encoding negative text ...', None)])
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n_txt = apply_style_negative(style_selction, negative_prompt)
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n_cond = pipeline.process_prompt(n_txt)
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outputs.append(['preview', (9, 'Encoding positive text ...', None)])
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p_txt = apply_style_positive(style_selction, prompt)
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p_cond = pipeline.process_prompt(p_txt)
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progressbar(3, 'Processing prompts ...')
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for i in range(image_number):
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tasks.append(dict(
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prompt=prompt,
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negative_prompt=negative_prompt,
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seed=seed + i,
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n_cond=n_cond,
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p_cond=p_cond,
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real_positive_prompt=p_txt,
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real_negative_prompt=n_txt
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))
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positive_basic_workloads = []
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negative_basic_workloads = []
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if use_style:
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for s in style_selections:
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p, n = apply_style(s, positive=prompt)
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positive_basic_workloads.append(p)
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negative_basic_workloads.append(n)
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else:
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for i in range(image_number):
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outputs.append(['preview', (5, f'Preparing positive text #{i + 1} ...', None)])
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current_seed = seed + i
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positive_basic_workloads.append(prompt)
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expansion_weight = 0.1
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negative_basic_workloads.append(negative_prompt) # Always use independent workload for negative.
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suffix = pipeline.expansion(prompt, current_seed)
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suffix = f'({suffix}:{expansion_weight})'
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print(f'[Prompt Expansion] New suffix: {suffix}')
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positive_basic_workloads = positive_basic_workloads + extra_positive_prompts
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negative_basic_workloads = negative_basic_workloads + extra_negative_prompts
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p_txt = apply_style_positive(style_selction, prompt)
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p_txt = safe_str(p_txt)
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positive_basic_workloads = remove_empty_str(positive_basic_workloads, default=prompt)
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negative_basic_workloads = remove_empty_str(negative_basic_workloads, default=negative_prompt)
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p_txt = join_prompts(p_txt, suffix)
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positive_top_k = len(positive_basic_workloads)
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negative_top_k = len(negative_basic_workloads)
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tasks.append(dict(
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prompt=prompt,
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negative_prompt=negative_prompt,
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seed=current_seed,
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real_positive_prompt=p_txt,
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))
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tasks = [dict(
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task_seed=seed + i,
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positive=positive_basic_workloads,
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negative=negative_basic_workloads,
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expansion='',
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c=[None, None],
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uc=[None, None],
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) for i in range(image_number)]
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outputs.append(['preview', (9, 'Encoding negative text ...', None)])
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n_txt = apply_style_negative(style_selction, negative_prompt)
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n_cond = pipeline.process_prompt(n_txt)
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if use_expansion:
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for i, t in enumerate(tasks):
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progressbar(5, f'Preparing Fooocus text #{i + 1} ...')
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expansion = pipeline.expansion(prompt, t['task_seed'])
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print(f'[Prompt Expansion] New suffix: {expansion}')
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t['expansion'] = expansion
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t['positive'] = copy.deepcopy(t['positive']) + [join_prompts(prompt, expansion)] # Deep copy.
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for i, t in enumerate(tasks):
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progressbar(7, f'Encoding base positive #{i + 1} ...')
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t['c'][0] = pipeline.clip_encode(sd=pipeline.xl_base_patched, texts=t['positive'],
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pool_top_k=positive_top_k)
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for i, t in enumerate(tasks):
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progressbar(9, f'Encoding base negative #{i + 1} ...')
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t['uc'][0] = pipeline.clip_encode(sd=pipeline.xl_base_patched, texts=t['negative'],
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pool_top_k=negative_top_k)
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if pipeline.xl_refiner is not None:
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for i, t in enumerate(tasks):
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progressbar(11, f'Encoding refiner positive #{i + 1} ...')
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t['c'][1] = pipeline.clip_encode(sd=pipeline.xl_refiner, texts=t['positive'],
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pool_top_k=positive_top_k)
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for i, t in enumerate(tasks):
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outputs.append(['preview', (12, f'Encoding positive text #{i + 1} ...', None)])
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t['p_cond'] = pipeline.process_prompt(t['real_positive_prompt'])
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t['real_negative_prompt'] = n_txt
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t['n_cond'] = n_cond
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progressbar(13, f'Encoding refiner negative #{i + 1} ...')
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t['uc'][1] = pipeline.clip_encode(sd=pipeline.xl_refiner, texts=t['negative'],
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pool_top_k=negative_top_k)
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if performance_selction == 'Speed':
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steps = 30
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@ -117,6 +151,7 @@ def worker():
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steps = 60
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switch = 40
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pipeline.clear_all_caches() # save memory
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width, height = aspect_ratios[aspect_ratios_selction]
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results = []
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@ -132,34 +167,32 @@ def worker():
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outputs.append(['preview', (13, 'Starting tasks ...', None)])
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for current_task_id, task in enumerate(tasks):
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imgs = pipeline.process_diffusion(
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positive_cond=task['p_cond'],
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negative_cond=task['n_cond'],
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positive_cond=task['c'],
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negative_cond=task['uc'],
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steps=steps,
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switch=switch,
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width=width,
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height=height,
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image_seed=task['seed'],
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image_seed=task['task_seed'],
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callback=callback)
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for x in imgs:
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d = [
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('Prompt', task['prompt']),
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('Negative Prompt', task['negative_prompt']),
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('Real Positive Prompt', task['real_positive_prompt']),
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('Real Negative Prompt', task['real_negative_prompt']),
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('Raw Mode', str(raw_mode)),
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('Style', style_selction),
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('Prompt', raw_prompt),
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('Negative Prompt', raw_negative_prompt),
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('Fooocus V2 Expansion', task['expansion']),
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('Styles', str(raw_style_selections)),
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('Performance', performance_selction),
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('Resolution', str((width, height))),
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('Sharpness', sharpness),
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('Base Model', base_model_name),
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('Refiner Model', refiner_model_name),
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('Seed', task['seed'])
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('Seed', task['task_seed'])
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]
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for n, w in loras:
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if n != 'None':
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d.append((f'LoRA [{n}] weight', w))
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log(x, d)
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log(x, d, single_line_number=3)
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results += imgs
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@ -106,13 +106,55 @@ refresh_loras([(modules.path.default_lora_name, 0.5), ('None', 0.5), ('None', 0.
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expansion = FooocusExpansion()
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def process_prompt(text):
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base_cond = core.encode_prompt_condition(clip=xl_base_patched.clip, prompt=text)
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if xl_refiner is not None:
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refiner_cond = core.encode_prompt_condition(clip=xl_refiner.clip, prompt=text)
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else:
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refiner_cond = None
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return base_cond, refiner_cond
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def clip_encode_single(clip, text, verbose=False):
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cached = clip.fcs_cond_cache.get(text, None)
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if cached is not None:
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if verbose:
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print(f'[CLIP Cached] {text}')
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return cached
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tokens = clip.tokenize(text)
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result = clip.encode_from_tokens(tokens, return_pooled=True)
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clip.fcs_cond_cache[text] = result
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if verbose:
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print(f'[CLIP Encoded] {text}')
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return result
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def clip_encode(sd, texts, pool_top_k=1):
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if sd is None:
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return None
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if sd.clip is None:
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return None
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if not isinstance(texts, list):
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return None
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if len(texts) == 0:
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return None
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clip = sd.clip
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cond_list = []
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pooled_acc = 0
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for i, text in enumerate(texts):
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cond, pooled = clip_encode_single(clip, text)
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cond_list.append(cond)
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if i < pool_top_k:
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pooled_acc += pooled
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return [[torch.cat(cond_list, dim=1), {"pooled_output": pooled_acc}]]
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def clear_sd_cond_cache(sd):
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if sd is None:
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return None
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if sd.clip is None:
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return None
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sd.clip.fcs_cond_cache = {}
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return
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def clear_all_caches():
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clear_sd_cond_cache(xl_base_patched)
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clear_sd_cond_cache(xl_refiner)
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@torch.no_grad()
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@ -5,7 +5,6 @@ from modules.path import fooocus_expansion_path
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fooocus_magic_split = [
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', extremely',
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', trending',
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', intricate,',
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]
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dangrous_patterns = '[]【】()（）|:：'
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@ -5,7 +5,7 @@ from PIL import Image
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from modules.util import generate_temp_filename
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def log(img, dic):
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def log(img, dic, single_line_number=3):
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date_string, local_temp_filename, only_name = generate_temp_filename(folder=modules.path.temp_outputs_path, extension='png')
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os.makedirs(os.path.dirname(local_temp_filename), exist_ok=True)
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Image.fromarray(img).save(local_temp_filename)
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@ -22,10 +22,10 @@ def log(img, dic):
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f.write(f"<p>{only_name}</p>\n")
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i = 0
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for k, v in dic:
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if i < 4:
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if i < single_line_number:
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f.write(f"<p>{k}: <b>{v}</b> </p>\n")
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else:
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if i % 2 == 0:
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if (i - single_line_number) % 2 == 0:
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f.write(f"<p>{k}: <b>{v}</b>, ")
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else:
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f.write(f"{k}: <b>{v}</b></p>\n")
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@ -1,16 +1,14 @@
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from modules.util import join_prompts
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fooocus_expansion = "Fooocus V2"
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default_styles = ["Default (Slightly Cinematic)"]
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# https://github.com/twri/sdxl_prompt_styler/blob/main/sdxl_styles.json
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styles = [
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{
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"name": "None",
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"prompt": "{prompt}",
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"negative_prompt": ""
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},
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{
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"name": "cinematic-default",
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"name": "Default (Slightly Cinematic)",
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"prompt": "cinematic still {prompt} . emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
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"negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured"
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},
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@ -926,8 +924,20 @@ styles = [
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}
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]
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styles = {k['name']: (k['prompt'], k['negative_prompt']) for k in styles}
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default_style = styles['None']
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def normalize_key(k):
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k = k.replace('-', ' ')
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words = k.split(' ')
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words = [w[:1].upper() + w[1:].lower() for w in words]
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k = ' '.join(words)
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k = k.replace('3d', '3D')
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k = k.replace('Sai', 'SAI')
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k = k.replace('(s', '(S')
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return k
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default_styles = [normalize_key(x) for x in default_styles]
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styles = {normalize_key(k['name']): (k['prompt'], k['negative_prompt']) for k in styles}
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style_keys = list(styles.keys())
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SD_XL_BASE_RATIOS = {
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@ -962,11 +972,6 @@ SD_XL_BASE_RATIOS = {
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aspect_ratios = {str(v[0]) + '×' + str(v[1]): v for k, v in SD_XL_BASE_RATIOS.items()}
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def apply_style_positive(style, txt):
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p, n = styles.get(style, default_style)
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return p.replace('{prompt}', txt)
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def apply_style_negative(style, txt):
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p, n = styles.get(style, default_style)
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return join_prompts(n, txt)
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def apply_style(style, positive):
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p, n = styles[style]
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return p.replace('{prompt}', positive), n
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@ -3,6 +3,13 @@ import random
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import os
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def remove_empty_str(items, default=None):
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items = [x for x in items if x != ""]
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if len(items) == 0 and default is not None:
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return [default]
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return items
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def join_prompts(*args, **kwargs):
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prompts = [str(x) for x in args if str(x) != ""]
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if len(prompts) == 0:
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@ -1,3 +1,13 @@
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### 2.0.0
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* V2 released.
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* completely rewrite text processing pipeline (higher image quality and prompt understanding).
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* support multi-style.
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* In 100 tests (prompts written by ChatGPT), V2 default results outperform V1 default results in 87 cases, evaluated by two human.
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* In 100 tests (prompts written by ChatGPT), V2 prompt understanding outperform V1 prompt understanding in 81 cases, evaluated by two human, in both default setting and multi/single style mode.
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* Because the above number is above 80%, we view this as a major update and directly jump to 2.0.0.
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* Some other things are renamed.
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### 1.0.67
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* Use dynamic weighting and lower weights for prompt expansion.
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15
webui.py
15
webui.py
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@ -8,7 +8,7 @@ import fooocus_version
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import modules.html
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import modules.async_worker as worker
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from modules.sdxl_styles import style_keys, aspect_ratios
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from modules.sdxl_styles import style_keys, aspect_ratios, fooocus_expansion, default_styles
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def generate_clicked(*args):
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@ -76,11 +76,10 @@ with shared.gradio_root:
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seed_random.change(random_checked, inputs=[seed_random], outputs=[image_seed])
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with gr.Tab(label='Style'):
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raw_mode_check = gr.Checkbox(label='Raw Mode', value=False,
|
||||
info='Similar to Midjourney\'s \"raw\" mode.')
|
||||
style_selction = gr.Radio(show_label=True, container=True,
|
||||
choices=style_keys, value='cinematic-default', label='Image Style',
|
||||
info='Similar to Midjourney\'s \"--style\".')
|
||||
style_selections = gr.CheckboxGroup(show_label=False, container=False,
|
||||
choices=[fooocus_expansion] + style_keys,
|
||||
value=[fooocus_expansion] + default_styles,
|
||||
label='Image Style')
|
||||
with gr.Tab(label='Advanced'):
|
||||
with gr.Row():
|
||||
base_model = gr.Dropdown(label='SDXL Base Model', choices=modules.path.model_filenames, value=modules.path.default_base_model_name, show_label=True)
|
||||
|
|
@ -110,8 +109,8 @@ with shared.gradio_root:
|
|||
|
||||
advanced_checkbox.change(lambda x: gr.update(visible=x), advanced_checkbox, right_col)
|
||||
ctrls = [
|
||||
prompt, negative_prompt, style_selction,
|
||||
performance_selction, aspect_ratios_selction, image_number, image_seed, sharpness, raw_mode_check
|
||||
prompt, negative_prompt, style_selections,
|
||||
performance_selction, aspect_ratios_selction, image_number, image_seed, sharpness
|
||||
]
|
||||
ctrls += [base_model, refiner_model] + lora_ctrls
|
||||
run_button.click(fn=refresh_seed, inputs=[seed_random, image_seed], outputs=image_seed)\
|
||||
|
|
|
|||
Loading…
Reference in New Issue